ArticleBritish journal of cancer2025
Serum multiomics prediction of prognosis and adverse reactions to concurrent chemoradiotherapy in patients with esophageal cancer.
Article in British journal of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development of Diagnostic Models and Biomarker Identification for Type 1 Leptomeningeal Metastasis in Lung Adenocarcinoma Using Olink: Exploratory Cohort Study with Internal Temporal Validation.Molecular diagnosis & therapy · 2026Article
- Review
- Unraveling role of arginine-NO metabolism by targeting HIF-1α signaling in mediating esophageal squamous cell carcinoma.Frontiers in molecular biosciences · 2026Article
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Authors and funding
11 authors.
Funding
Abstract
objectiveConcurrent chemoradiotherapy (CCRT) is an important treatment for patients with locally advanced esophageal squamous cell carcinoma (ESCC). There is still a lack of reliable means to predict efficacy, prognosis and hematologic toxicity.
designWe analyzed 127 serum samples before CCRT and 93 serum samples after CCRT from 127 ESCC patients via metabolomics by GC-MS. Combined with Olink proteomics, we constructed models to predict response and survival through machine learning. Multiple linear regression was used to construct hematologic toxicity prediction models. In combination with the proteomics of ESCC, metabolic changes were studied.
resultsA prediction model for the efficacy to CCRT was established via serum metabolomics and proteomics (Train, CR/nCR = 28/50, AUC = 0.9848, 95% CI = 0.9639-1.0000; Test, CR/nCR = 17/15, AUC = 0.8854, 95% CI = 0.7800-0.9908). A survival prediction model was established (n = 109, C-index = 0.7640, 95% CI = 0.7140-0.8140). Linear models for predicting hematologic toxicity were constructed (n = 111, R > 0.7). L-serine is important for the prognosis of patients with ESCC treated with CCRT, and SHMT2 is a key protein in serine metabolism that affects the efficacy of CCRT.
conclusionThe combination of serum metabolomics with proteomics can effectively predict the prognosis and hematologic toxicity, which can provide important data for patients to choose treatment methods.
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